Amazon takes advantage of consumers’ desire for convenience and the blurred lines between online and offline experiences with Amazon Go. The prototype store opened in Seattle last week, with people lining up to check out the cashless, cashless brick-and-mortar store, where customers can just walk in, grab whatever they want and leave. All transactions are processed seamlessly through in-store systems and the Amazon Go mobile app. According to the Amazon Go website, “All you need is an Amazon account, the free Amazon Go app and latest generation iPhone or Android phone. “
Retailers who have yet to take full advantage of consumer use of mobile devices should pay attention to the results of Amazon Go and other mobile commerce trials. Delivering mobile experiences provides a great starting point for breaking down the separation between offline and online retail channels.
Follow the example of Amazon Go
Amazon Go is the current pinnacle of efforts to cloud in-store and online experiences (read my article on Amazon’s acquisition of Whole Foods for how Amazon has evolved its investment in this area). Seattle’s mini-grocery store is built on the mobile device retail model that powers face-to-face commerce – the concept that you can buy something without having to pull out a wallet to do so.
When customers arrive at the Amazon Go store, their phones trigger a sensor turnstile when they enter. Customers then select their products as they would in any boutique grocery store (offerings include wine, beverages, produce, meat, sandwiches, and salads). Each item is coded to help in-store cameras, scanners and infrared sensors detect selections. Once they have finished shopping, customers simply exit through the turnstiles of the sensors; the Go app processes their transactions and they get digital receipts on their phones.
Experiments like Amazon Go create data in real time. In most mobile commerce operations, information is collected through smartphone systems such as apps or chatbots. In the Amazon Go store, data acquisition comes from cameras and sensors that track inventory and customer activity. Marketers are primarily interested in aggregate data showing trends in customer activity – the information Amazon collects from the Go experience could improve predictive analytics models behind customer-centric services. If the concept takes off and Amazon opens more Go stores, it’s not hard to imagine that the company could refine its algorithms so that they can tell customers where the Amazon Go is the most. close and help them find their favorite product choices.
For many, mobile is the only way to go
A look at global markets reveals how essential a combined mobile-offline operation could be to retail strategy. A lot of people only have mobile devices because they can’t afford a laptop or desktop computer. The end result is the rapid adoption of mobile services in places like China. Alibaba, the China-based tech giant that rivals Amazon in e-commerce and cloud platforms, has boosted mobile payments alongside another major player in China, Tencent.
Alibaba’s Alipay payment platform controls a significant percentage of the mobile payments market, according to Asian Nikkei Review. The acceptance of the smartphone market as a mainstream device means that retailers and other businesses should eliminate operational divisions between online and offline businesses if they are to compete globally.
Consumer acceptance of smartphones has also changed customer expectations for service after an online discovery or purchase. This change inspired the evolution of analytics. In its boom, analysis provided observational metrics – which could be observed from web page activity.
But as people learned to use smartphones to search online, they also expanded engagement activity, first through the use of social media, and later apps. and chatbots. Consumers first turned to their phones, creating real-time data and the real instances associated with the data. All of this shifted from observational metrics to a more attribution-influenced analysis meant to piece together the story behind a customer’s experiences before a click. The need to add a statistical approach to attribution led to predictive analytics. It also spawned new thinking among savvy marketers: viewing online activity as an integral part of marketing attribution as a whole and a key part of budget decisions.
Start small with online / offline experiences
Managers who don’t know where to start to mix online and offline operations should consider small-scale, personalized initiatives. Just as Amazon started Amazon Go with a single store, marketers need to think about what tasks can be simplified for the convenience of their customers, then look at how that service is delivered and take small steps toward that goal. Some issues may not be apparent at first, but looking at the results of a trial period can reveal which processes need improvement.
Another step is to apply analytics with special attention to attribution. Marketers can better understand attribution of sales activity and bottlenecks in small-scale retail launches.
The analytics platform should also be a building block of a predictive analytics stack in which data from different sources can be mixed.
A predictive analytics model can ultimately provide dynamic forecasting advice in determining where and when to send an offer. Better forecasting will also highlight inventory issues, leading to better discussions about operational resources.
Consumer behavior based on viewing a product online and then visiting a store to pick up that item is now a retail standard. RetailDiving notes that, according to a report from the National Retail Federation’s Consumer View tracking service, 70% of shoppers are familiar with mobile payment capabilities and the BOPIS (online purchase, store pickup) model. This awareness has manifested itself in the sales of retailers agile enough to mix online and offline experiences, beating out competitors that may soon find themselves bankrupt.
Thus, marketers should expect more experiences like Amazon Go to provide an experience that can complement personal use of smartphones. It also means marketers no longer need to see ecommerce as a separate channel, as buyers today don’t see it that way. For them, online business is just business.
Pierre DeBois is the founder of Zimana, a digital analysis consulting firm for small businesses. It examines data from web analytics and social media dashboard solutions, then provides web development recommendations and actions that improve business marketing strategy and profitability.